IDEAS home Printed from https://ideas.repec.org/a/fgv/eaerae/v62y2022i6a86715.html

Featured topics in research on digital transformation: Evidence from bibliometric study and content analysis

Author

Listed:
  • Figueiredo Facin, Ana Lucia
  • Franco Paes Leme Barbosa, Ana Paula
  • Matsumoto, Cristiane
  • Safady da Gama Cruz, Ana Flavia
  • Salerno, Mario Sergio

Abstract

Digital transformation (DT) arises in debates about trends in various industries, mainly in value creation through the innovation of products and services and how they are negotiated. DT poses new challenges to organizations, which this research aims to identify by answering: What is the structure of the literature on DT, and what themes have gained prominence in the last five years? This research conducted a systematic literature review with bibliometric analysis and content analysis. The bibliometric analysis highlighted the following discussions: strategic renewal amid DT; implementation of technologies in Industry 4.0; digitization to enable servitization; DT as an engine of innovation in business models; digital innovation management; and DT to change the consumer experience. The analyses point out avenues for further research and raise important questions for decision-makers in companies that want to reap the benefits of DT.

Suggested Citation

  • Figueiredo Facin, Ana Lucia & Franco Paes Leme Barbosa, Ana Paula & Matsumoto, Cristiane & Safady da Gama Cruz, Ana Flavia & Salerno, Mario Sergio, 2022. "Featured topics in research on digital transformation: Evidence from bibliometric study and content analysis," RAE - Revista de Administração de Empresas, FGV-EAESP Escola de Administração de Empresas de São Paulo (Brazil), vol. 62(6), August.
    • Handle: RePEc:fgv:eaerae:v:62:y:2022:i:6:a:86715
    as

    Download full text from publisher

    File URL: https://periodicos.fgv.br/rae/article/view/86715
    Download Restriction: no
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:fgv:eaerae:v:62:y:2022:i:6:a:86715. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Núcleo de Computação da FGV EPGE (email available below). General contact details of provider: https://edirc.repec.org/data/eagvfbr.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.